Improved speaker adaptation using text dependent spectral mappings.
Ming-Whei Feng, Francis Kubala, Richard M. Schwartz, John I. Makhoul · International Conference on Acoustics, Speech, and Signal Processing · 1988
of speaker adaptation is to minmize the amount v Models to model the speech from the new speaker d in high recognition accuracy with a grammar of ce, we investigate a new probabdistic spectral edure to estimate the transformation. To evaluate rithm, recognition expenments are carried out on 1000-word resource management continuous ase using a grammar with perplexity 60. The that significant unprovement in recognition has been achieved compared to our previous adaptation algorithm. The average word error rate of speakeradapted models using 2 minutes of training speech is 11.3% compared to 7.1% for speaker-dependent models using 20-28